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Related Experiment Videos

Geometry-driven photorealistic facial expression synthesis.

Qingshan Zhang1, Zicheng Liu, Baining Guo

  • 1Research and Innovation Center, Alcatel Shanghai Bell Ltd, Pudong, Shanghai. Qingshan.ZHANG@alcatel-sbell.co.cn

IEEE Transactions on Visualization and Computer Graphics
|December 31, 2005
PubMed
Summary

This study introduces a geometry-driven system for facial expression synthesis, overcoming limitations of expression mapping by generating realistic skin details like wrinkles. It also infers missing feature points for enhanced facial animation and editing.

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Area of Science:

  • Computer Graphics
  • Computer Vision
  • Human-Computer Interaction

Background:

  • Expression mapping is a common technique for facial animation but fails to capture fine details like wrinkles.
  • Existing methods lack the ability to generate photorealistic expression details from geometric data alone.

Purpose of the Study:

  • To develop a geometry-driven facial expression synthesis system that generates photorealistic expression details.
  • To address the challenge of insufficient feature points in performance-driven animation by inferring missing data.
  • To enable interactive facial expression editing with realistic skin deformations.

Main Methods:

  • Developed a novel geometry-driven facial expression synthesis system.
  • Implemented an example-based approach to infer missing feature point motions from a tracked subset.

Related Experiment Videos

  • Enabled interactive expression editing by allowing users to manipulate feature points.

    • Main Results:

    • The system successfully synthesizes facial expressions with photorealistic and natural-looking details, including wrinkles.
    • The technique for inferring missing feature points enhances the applicability of geometry-driven synthesis.
    • Interactive editing demonstrates the system's capability for real-time facial expression generation with skin deformation.

    Conclusions:

    • The proposed geometry-driven system effectively overcomes the limitations of traditional expression mapping.
    • The method provides a robust solution for synthesizing detailed and natural facial expressions.
    • This work advances facial animation and opens new possibilities for interactive expression editing.